Geoinformatics based LULUCF inputs for CDM Project of ITC - PSPD, Bhadrachalam

CDM Barrier removal – Meet III

Forestry and Ecology DivisionNational Remote Sensing Agency

Dept. of Space

Pujar GS, Sudhakar, S & Murthy MSR

Unutilized Agriculture Plantations Scrub Forest Others

Unutilized

Agriculture

Plantations

Scrub

Forest

Others

Land use/cover change matrix required to be addressed as per

Good Practice Guidelines (IPCC)

Severe degree negative change

Best possible positive change

Moderate negative change

Moderate degree positive change

Snapshot of landscape at the start of the project

Spatial explicitness of boundaries

Amenability for spatial modeling to prove additionality

Potential to collate multisource information for barrier reduction

0% 20% 40% 60% 80% 100%

Leakage

Additionality

Biomass Pattern

Land cover

change

Sink boundaries

RS GIS GPS

*

* SCALE DEPENDENTRS med res & h-res

1990

2000

2001

2002

2003

2004

2005

2010

Reforestation Compliance

Project Period

Prediction/Addnlty

Plantation growth

Geomatics Compatibility

Afforestation – Requires assessment data using 50 year old data

Satellite data not available for the period

Compilation of such data if exists in to spatial form needs separate

effort, 1955 2005? LISS

III/IV

Reforestation – Requires assessment data using data since 31st Dec 1989

Assessment of non forest lands possible using available IRS data

during 19901990

2005LISS I/II/ TM

LISS III/IV

forest

agril

Nonforest

Appraisal of technology potential to PDD facilitator

Selection of satellite datasets suiting the requirement

Image analysis for land cover delineation and plantation mapping

Plantation mapping aided by ground based ownership Information

Generation of sink boundaries and erstwhile land cover content

Prediction of plantation position and spread

Sink boundary and position for validation

Information fine tuning for final submission

Social forestry or similar initiative generally has to occupy smaller Land parcels due to socio-economic factors connected to it

Marginal lands means relatively higher probability of constrainedsuccess. Generally lands prevail adjacent to slopy/forest area & hence may not be best habitat available.

These factors result in mixed response of reflectances at sensorLevel and hence will induce difficulty in mapping

Promoted plantations may not have copy-book implementationOf package of practices

IRS P6 LISS III data

MAR 2005

IRS P6 LISS III data

MAR 2005

Image enhancements

Pre-fieldinterpretation

IRS 1D LISS III data

APR 2004

Field Check

Discussion Interpretation

Social Foresty Plantation mapping

Land cover classification for SF windows

LandsatTM/ETM data

OCT 1990

Reforestation inputs for CER’s

GPS based inventory

GPS based inventory

supportive

NOV 2000 SF windowsSocial forestry

PlantationWindows in the

Study site

IRS P6 LISS III data

MAR 2005

IRS P6 LISS III data

MAR 2005

Image enhancements

Pre-fieldinterpretation

IRS 1D LISS III data

APR 2004

Field Check

Discussion Interpretation

Social Foresty Plantation mapping

Land cover classification for SF windows

LandsatTM/ETM data

OCT 1990

Reforestation inputs for CER’s

GPS based inventory

GPS based inventory

GPS based inventory

GPS based inventory

supportive

NOV 2000 SF windowsSocial forestry

PlantationWindows in the

Study site

Methodology for land cover change in Social Forestry Mandals

Vegetation and Land cover 1990

Vegetation and Land cover 2005

Land coverChanges

Plantationincrease

Rate of increaseIn 5 km pixels

Categorization of Rates

Stratified random Allocation of sites

Suitability Surface

Scrub and adjacency

Amenable slopes inAmenable elevations

Forest area exclusion

Size based buffers

Site delineation

Probability of sitesElimination of smallpatches

PlantationSite predictions

Predictingof plantationOccurrence

Approach

Thank you